Background

Early mobility interventions in intensive care units (ICUs) are safe and improve outcomes in subsets of critically ill adults. However, implementation varies, and the optimal mobility dose remains unclear.

Objective

To test for associations between daily dose of out-of-bed mobility and patient outcomes in different ICUs.

Methods

In this retrospective cohort study of electronic records from 7 adult ICUs in an academic quarternary hospital, multivariable linear regression was used to examine the effects of out-of-bed events per mobility-eligible day on mechanical ventilation duration and length of ICU and hospital stays.

Results

In total, 8609 adults hospitalized in ICUs from 2015 through 2018 were included. Patients were mobilized out of bed on 46.5% of ICU days and were eligible for mobility interventions on a median (IQR) of 2.0 (1–3) of 2.7 (2–9) ICU days. Median (IQR) out-of-bed events per mobility-eligible day were 0.5 (0–1.2) among all patients. For every unit increase in out-of-bed events per mobility-eligible day before extubation, mechanical ventilation duration decreased by 10% (adjusted coefficient [95% CI], −0.10 [−0.18 to −0.01]). Daily mobility increased ICU stays by 4% (adjusted coefficient [95% CI], 0.04 [0.03–0.06]) and decreased hospital stays by 5% (adjusted coefficient [95% CI], −0.05 [−0.07 to −0.03]). Effect sizes differed among ICUs.

Conclusions

More daily out-of-bed mobility for ICU patients was associated with shorter mechanical ventilation duration and hospital stays, suggesting a dose-response relationship between daily mobility and patient outcomes. However, relationships differed across ICU subpopulations.

Notice to CE enrollees

This article has been designated for CE contact hour(s). The evaluation demonstrates your knowledge of the following objectives:

  1. Describe the out-of-bed eligible (OOB-E) index as a method to quantify mobility interventions.

  2. Understand the effect of daily mobility on mechanical ventilation and length-of-stay outcomes.

  3. Describe how daily mobility prevalence differs by intensive care unit subpopulations.

To complete the evaluation for CE contact hour(s) for activity A2452, visit https://aacnjournals.org/ajcconline/ce-articles. No CE fee for AACN members. See CE activity page for expiration date.

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Early mobility interventions in intensive care units (ICUs) are safe and improve patient outcomes in subsets of critically ill adults.13  Many institutions have created ICU mobility programs; however, the optimal amount of mobility to influence patient outcomes remains unclear due to the heterogeneity of ICU patient populations (other than in randomized controlled trials) and a lack of standardized quantitative reporting of mobility interventions.

Implementation also varies widely; most ICU mobility interventions are based on protocols with individualized, functional activities adjusted to a patient’s tolerance and exercise capacity.3,4  Documentation of the type, frequency, intensity, and duration of mobility, or mobility “dose,” is often missing.58  In recent meta-analyses, only 14% of randomized controlled trials reported any mobility dose,6  and reporting of the intervention dose was insufficient.5 

No consensus on how to best measure and report ICU mobility dose across studies, institutions, and populations exists. Methods to measure ICU mobility dose vary widely and include highest level of mobility achieved,9,10  percentage of days mobilized out of bed,1113  mobility events per day,14  cumulative days of mobility,6  time to first mobility intervention,1  and completion of a mobility eligibility assessment.1517  No methods address all domains of mobility dose. Although new methods to quantify mobility, such as actigraphy, may help improve reporting, the lack of standardized measures to quantify mobility across multiple dimensions7,18,19  limits our ability to characterize potential dose-response relationships,5,6  rendering translation of mobility research into clinical guidelines challenging.20 

Methods to measure ICU mobility dose vary widely.

With widespread adoption of electronic health record (EHR) systems, institutions are increasingly able to capture clinical mobility data in large ICU populations. We previously showed that clinician documentation in the EHR can be used to accurately represent the frequency of ICU out-of-bed mobility events, including sitting out of bed and walking.21  The objectives of this study were to (1) use EHR-derived descriptors of the type and frequency of mobility interventions to determine the prevalence of out-of-bed events per ICU day across multiple ICUs; (2) test for associations between out-of-bed mobility dose and patient outcomes in a large, real-world ICU population; and (3) compare effects of mobility dose in patient subpopulations, including patients in different ICUs and those receiving mechanical ventilation. We hypothesized that an increase in daily out-of-bed mobility events would be associated with reduced duration of mechanical ventilation and shorter ICU and hospital stays.

We conducted a retrospective cohort study of ICU mobility practices and patient outcomes across 7 adult ICUs at an academic quaternary hospital among patients hospitalized from December 2015 through October 2018. Our ICU mobility program was launched in 2012 and became the standard of care in 2015.22  In December 2015, descriptors of mobility activities were added to our EHR as structured flow sheet fields for documentation. Our institutional review board approved this study (No. 1306549) and we followed Strengthening the Reporting of Observational Studies in Epidemiology guidelines.

Patients at least 18 years old who were admitted to an adult ICU for the first time during the study period were eligible for inclusion. We identified eligible ICU patient admissions in which patients received an ICU level of care and had an ICU stay of at least 24 hours. Exclusion criteria are detailed in Figure 1.

Data Sources

All data were extracted from our adult critical care registry based on EHR-derived data (Epic Systems Corporation). The study team developed a rules-based algorithm using these EHR-derived fields to count the number of out-of-bed mobility events that patients in the ICU completed. We defined out-of-bed events as documented episodes in which the patient was sitting at the edge of the bed, on a cardiac/stretcher chair, on a commode, or on a bedside chair; standing at the bedside; marching in place; sidestepping; or walking. We chose out-of-bed events as the primary exposure variable because of prior research showing that out-of-bed events were represented more accurately in the EHR than were less intensive subtypes of mobility21  and because using out-of-bed events aligned with previous point-prevalence studies.12,13,23  See the Supplement (available online only at ajcconline.org) for details regarding development and validation of the mobility algorithm.24 

Study Variables

Using the consensus article by Hodgson et al25  describing safety criteria for out-of-bed mobility, we identified respiratory, cardiovascular, neurologic, and other safety considerations that we could reliably acquire from EHR data to determine ICU days on which a patient was ineligible for out-of-bed mobility because mobility was deemed unsafe. Mobility-eligible days were defined as ICU days on which any of the following were not present: median heart rate of less than 60/min or greater than 120/min; median fraction of inspired oxygen of greater than 0.6; positive end-expiratory pressure of greater than 12 cm H2O; median Richmond Agitation-Sedation Scale score of less than −2 or greater than +2; median Glasgow Coma Scale score of less than 8; administration of an inotrope/vasopressor (epinephrine, dopamine, dobutamine, milrinone, phenylephrine, norepinephrine, or vasopressin) or cisatracurium infusion; median hemoglobin level of less than 7.0 g/dL; or receipt of comfort care or hospice services.

Out-of-bed mobility events were quantified according to event frequency and normalized using ICU mobility-eligible days. We defined daily mobility dose in 2 ways: (1) out-of-bed eligible (OOB-E) index (number of out-of-bed mobility events on eligible days divided by number of mobility-eligible ICU days) and (2) for patients who had ever received mechanical ventilation, OOB-E before extubation index (number of out-of-bed mobility events on eligible days from ICU admission to day of last extubation divided by number of mobility-eligible ICU days from ICU admission to day of last extubation) (see Supplement, available online only).

Our primary outcome was mechanical ventilation duration. Prespecified secondary outcomes were ICU and hospital length of stay (LOS), in alignment with previous studies. The duration of mechanical ventilation for each patient was ascertained from EHR data using an algorithm developed and validated by the Data Provisioning Core of the Data Center of Excellence at University of California, Davis, Health. This algorithm used combinations of mechanical ventilation mode, settings, and patient parameters to identify start and stop times of mechanical ventilation (Supplemental Table 1, available online only). Intensive care unit LOS and hospital LOS were determined on the basis of bed admission, discharge, and transfer record time stamps. Intensive care unit LOS was defined as the time from ICU admission to a downgrade in level of care, as indicated by an order for medical/surgical or telemetry transfer. We used the downgrade time rather than the time a patient physically left the ICU to account for fluctuations in hospital throughput that might have caused the number of ICU days to reflect non-ICU bed availability rather than patient acuity (see Supplemental Table 2, available online only).

Mobility was quantified by dividing out-of-bed event frequency by ICU mobility-eligible days.

Statistical Analysis

Quantitative variables were summarized as means with SDs or medians with IQRs; categorical variables were summarized as proportions. The following variables were extracted from the EHR to adjust for potential confounding: age, sex, body mass index, severity of illness according to the Sequential Organ Failure Assessment score in the first 24 hours after ICU admission,26  weighted Elixhauser comorbidity scores,27  functional status on hospital admission (defined as independent, needs assistance, or dependent), comfort care/hospice status; ICU type (surgical, medical, medical/surgical, neurosurgical, burn, or cardiothoracic), use of mechanical ventilation during ICU stay, and days to first out-of-bed event. These variables were included in the model because of their potential to confound the associations between the primary exposure variable and the outcomes.

We used multivariable linear regression to investigate the associations between mobility daily dose and mechanical ventilation duration, ICU LOS, and hospital LOS. For ICU and hospital LOS, we evaluated the effect of mobility dose (OOB-E index) for the full cohort and the effect of mobility dose before extubation (OOB-E before extubation index) for patients who received mechanical ventilation. For all outcomes, we used prespecified sensitivity analyses to evaluate the effect of out-of-bed mobility dose among ICU survivors. Prespecified subgroup analyses were performed for each ICU type by including an interaction term between ICU type and mobility dose. These subgroups were based on evidence that mobility effectiveness varies across ICU patient subpopulations28,29  and that mobility may be more effective for ICU patients who receive mechanical ventilation.1,4  Outcomes were log transformed to meet model assumptions. All covariates were included as main effects. Analyses were conducted with Stata, version 13 (StataCorp LP).

In total, 8609 adults hospitalized in an ICU were included in the study (Figure 1). Patient characteristics stratified by use of mechanical ventilation during the ICU stay are shown in Table 1, and patient characteristics stratified by type of ICU are shown in Supplemental Table 3 (available online only).

Out-of-Bed Mobility Prevalence

Table 2 provides descriptive information for out-of-bed mobility events performed throughout the ICU hospitalization. Patients were mobilized out of bed on 46.5% of ICU days, and 5957 patients (69.2%) had at least 1 out-of-bed mobility event while in the ICU. Patients were eligible for mobility interventions on a median (IQR) of 2.0 (1–3) ICU days, out of a median (IQR) ICU stay of 2.7 (2–9) days. Patients receiving mechanical ventilation were eligible for out-of-bed mobility on a median (IQR) of 1 (0–2) day from ICU admission to the day of extubation. The most common reasons for ineligibility for out-of-bed mobility in the ICU were vasopressor use, receipt of comfort care, and median Richmond Agitation-Sedation Scale score of less than −2 or greater than +2 (Supplemental Table 4, available online only).

The median (IQR) OOB-E index was 0.5 (0–1.2) events per day among all adults hospitalized in the ICU. The median OOB-E index was higher in predominately surgical ICUs (cardiothoracic, neurosurgical, surgical, and burn ICUs) than in medical and mixed medical/surgical ICUs, largely because of daily out-of-bed mobility interventions performed in the cardiothoracic and burn ICUs (Figure 2). Of the 3443 patients who received mechanical ventilation, 569 (16.6%) achieved an out-of-bed mobility event during mechanical ventilation. The median (IQR) OOB-E before extubation index was 0 (0–0.2) events per day among patients who received mechanical ventilation.

Mechanical Ventilation Duration

The daily dose of mobility for patients receiving mechanical ventilation, according to the OOB-E before extubation index, was inversely associated with mechanical ventilation duration (Table 3). For every unit increase in the OOB-E before extubation index, hours receiving mechanical ventilation decreased by 10% (adjusted coefficient [95% CI], −0.10 [−0.18 to −0.01]). The association was driven by the effect in the medical ICU, in which each unit increase in the OOB-E before extubation index was associated with a 22% reduction in mechanical ventilation duration. The OOB-E before extubation index was not significantly associated with mechanical ventilation duration in the other ICUs. See Supplemental Tables 5 and 6 (available online only) for regression main effects, interaction terms, and covariate regression coefficients. When we limited the analysis to hospital survivors across all ICUs, we did not observe a significant association between OOB-E index and mechanical ventilation duration (coefficient [95% CI], −0.05 [−0.13 to 0.03]) (Supplemental Table 7, available online only). However, among survivors in the medical ICU, the significant association with reduced mechanical ventilation duration held (coefficient [95% CI], −0.23 [−0.43 to −0.03]).

Length of Stay

Overall, the daily dose of out-of-bed mobility was associated with longer ICU stays (Table 3). For every unit increase in the OOB-E index (events per day), ICU LOS increased by 4%. This association was predominately driven by the burn, cardiothoracic, and neurosurgical ICUs, in each of which the OOB-E index was positively associated with ICU LOS (Table 3). Daily dose of out-of-bed mobility was not associated with ICU LOS in the other ICUs. Daily dose of out-of-bed mobility was similarly associated with longer ICU stays among hospital survivors (6% increase in ICU LOS) (Supplemental Table 7, available online only) and patients who did not receive mechanical ventilation (5% increase in ICU LOS) (Supplemental Table 8, available online only). When examining the association between mobility dose and ICU LOS in patients who received mechanical ventilation, we found that each out-of-bed mobility event per eligible day performed before extubation was associated with an 8% decrease in ICU LOS (coefficient [95% CI], −0.08 [−0.13 to −0.02]) (Supplemental Table 9, available online only).

Daily dose of ICU out-of-bed mobility was inversely associated with hospital LOS. For every unit increase in the OOB-E index, hospital LOS decreased by 5%. In 4 of the 7 ICUs, an increase in OOB-E index was inversely associated with hospital LOS, with reductions in LOS ranging from 5% to 11% (Table 3). The association was similar when the analysis was limited to hospital survivors, with a reduction in hospital LOS by 5% (coefficient [95% CI], −0.05 [−0.07 to −0.04]) (Supplemental Table 7, available online only). Among patients who received mechanical ventilation, each out-of-bed mobility event per eligible day performed before extubation was associated with an 11% decrease in hospital LOS (coefficient [95% CI], −0.11 [−0.16 to −0.06]) (Supplemental Table 9, available online only).

We analyzed EHR data from 8609 patients in 7 adult ICUs to determine associations between the number of out-of-bed mobility events and key patient outcomes. Overall, we found that each additional out-of-bed event performed per mobility-eligible day conferred a 10% decrease in mechanical ventilation duration, a 4% increase in ICU LOS, and a 5% decrease in hospital LOS. The effect in the medical ICU appeared to drive the association between increased mobility dose and lower mechanical ventilation duration. Despite the association with longer ICU stays among all patients, we found the opposite effect among patients receiving mechanical ventilation, for whom daily out-of-bed mobility before extubation was associated with shorter ICU stays. Although these findings provide support for a dose-response relationship between daily mobility and patient outcomes, our finding that associations were not consistent across all subpopulations has important implications.

Our findings regarding associations between mobility and mechanical ventilation duration, ICU LOS, and hospital LOS are consistent with those of some but not all prior studies. We found shorter mechanical ventilation duration and hospital stays with higher doses of mobility, similar to the findings of recent meta-analyses examining functional mobility exercises.5,6,30,31  However, our findings related to ICU LOS differ from those of meta-analyses that reported an overall decrease in ICU LOS by 0.8 to 1.8 days.5,6,32  The increase in ICU LOS in our study might be explained by our inclusion of patients in burn, cardiothoracic, and neurosurgical ICUs and patients who did and did not receive mechanical ventilation. Meta-analyses of studies of patients in specialty ICUs also failed to find significant associations between mobility and ICU LOS in patients treated for trauma30  and patients after cardiac surgery.33  Furthermore, ICU LOS may have been impacted by institutional practices whereby some specialty ICUs can continue providing patients with ICU-level nursing care or monitoring despite improvement in critical illness. These findings suggest that future research should consider subpopulations of patients in subspecialty surgical ICUs separately.

Our results also suggest that the timing of out-of-bed mobility may be important. Although out-of-bed mobility events were associated with longer ICU stays overall, out-of-bed mobility events performed before extubation in patients undergoing mechanical ventilation were associated with decreased mechanical ventilation duration and shorter hospital and ICU stays. Hospital survivors in the medical ICU had a significantly shorter duration of mechanical ventilation with each additional out-of-bed event performed per mobility-eligible day while intubated. Although the CI for this finding was wide, the 23% reduction in mechanical ventilation hours may be clinically meaningful, especially for patients with longer mechanical ventilation durations. However, out-of-bed events for patients receiving mechanical ventilation were rare, despite overall high mobility rates in the general cohort, which aligns with published prevalence studies.34  Future research and quality initiatives should use approaches that recognize potential differences in mobility dose across phases of hospitalization (eg, before extubation and after ICU discharge).

Few randomized controlled trials to date have tested for a dose-response relationship between ICU mobility and clinical outcomes.14,28,3537  Some studies suggest that low-intensity, once-daily mobility may reduce mechanical ventilation days and LOS, but these findings have not been consistent.1,6,28  The authors of a meta-analysis published in 2022 used mobility availability as a surrogate for mobility dose and compared mobility interventions with low-dose (<5 days per week) and high-dose (≥5 days per week) control group mobility. They found that in comparison with low-dose usual care mobility, mobility interventions reduced mechanical ventilation duration, ICU LOS, and hospital LOS. Comparatively, the effects were not sustained when the control group received high-dose mobility, which suggests that the association may not be linear, with diminishing benefit at higher doses.5  These findings are supported by those of a recent Australian and New Zealand Intensive Care Society randomized controlled trial that showed that high-intensity mobility, measured with the ICU Mobility Scale and activity minutes, resulted in no significant improvement in outcomes.37  Future studies may benefit from using a granular quantification of mobility, like the OOB-E index, that could be automatically calculated from existing clinical documentation, would fit into a vital sign monitoring paradigm, and might allow titration of mobility interventions to a target dose.

Several limitations should be considered when interpreting our findings. First, the results of our single-site study may not be generalizable to other institutions, especially those with exclusively mixed rather than subspecialized ICUs, or to patients treated during the COVID-19 pandemic. Although some of our findings are consistent with those of prior clinical trials, our results in the burn, cardiothoracic, and neurosurgical ICUs require replication before the association can be considered reliable. Second, our results might have been affected by unmeasured residual confounding despite our efforts to account for illness severity by using an acute severity of illness score, a prehospital comorbidity score, and an ICU admission functional status assessment. Third, we made several clinical assumptions that could have affected results, such as excluding patients with multiple ICU stays and defining patient subgroups by ICU location. Our literature-derived definition of mobility-eligible days did not capture all exclusion criteria for participating in out-of-bed mobility. For example, we may have excluded days when clinicians administered mobility interventions even when patients were receiving vasopressors, since our criteria were not dose related. However, we did not exclude patients on the basis of other relative contraindications, such as catheter, drain, or device location. Future studies should examine the effects of mobility on different patient subpopulations, including patients grouped by primary attending service, patients with multiple ICU stays, and patients with different reasons for immobility, because exclusions may differ by institution and unit culture. Out-of-bed event counts may not adequately capture the total dose of mobility in terms of intervention type, duration, and intensity. Fourth, the use of EHR data to identify mobility dose might have introduced bias. Fifth, we did not directly examine the threshold at which the effect of out-of-bed mobility events on outcomes diminishes, mobility performed outside the ICU, or other relevant outcomes such as discharge disposition, discharge functional status, or hospital-acquired conditions.

Our findings support a dose-response relationship; however, associations differed across ICU subpopulations.

This study was unique in its use of an algorithm to estimate a patient-level, daily dose of ICU out-of-bed mobility events. This algorithm allowed for analysis of mobility and patient outcomes in a large cohort, including common subgroups of patients in whom mobility is frequently applied but incompletely understood. Recent research, including this study, highlights clinical heterogeneity based on individual and organization-specific factors that calls into question the use of a single standard approach to delivering mobility therapies. How frequently, how intensively, and for how long therapy should be provided for people in different ICU subgroups are all important unanswered questions. Developing automated data science and informatics approaches for large-scale analysis of real-world data is likely to help refine the hypotheses that are ultimately selected for testing via randomized controlled trials.

Timing of out-of-bed mobility may be important; specifically, mobility done before extubation shortens mechanical ventilation duration.

In this retrospective study of EHR data from 8609 patients in the ICU, we found a 10% decrease in time receiving mechanical ventilation, a 4% increase in ICU LOS, and a 5% decrease in hospital LOS with each additional out-of-bed event per mobility-eligible day. Although these findings provide support for a dose-response relationship between daily ICU mobility and patient outcomes, associations were not consistent across all ICU populations, suggesting important implications for mobility research and translation to clinical practice. Future studies should examine additional methods to quantify the dose of mobility interventions across increasingly broad dimensions and in additional patient subpopulations, with considerations for how clinicians translate timing, duration, frequency, and activity types.

We gratefully acknowledge members of the Data Provisioning Core at UC Davis Health and the patients, families, and clinicians who participate in ICU mobility interventions every day.

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Footnotes

FINANCIAL DISCLOSURES

This research was supported by the UC Davis Clinical and Translational Science Center (National Center for Advancing Translational Sciences UL1 TR000002 and UL1 TR001860), the National Heart, Lung, and Blood Institute (T32 HL007013), and the UC Davis Data Center of Excellence, Data Provisioning Core. This study is an investigator-initiated study. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

 

SEE ALSO

For more about early mobility, visit the Critical Care Nurse website, www.ccnonline.org, and read the article by Bach and Hetland, “A Step Forward for Intensive Care Unit Patients: Early Mobility Interventions and Associated Outcome Measures” (December 2022).

 

To purchase electronic or print reprints, contact American Association of Critical-Care Nurses, 27071 Aliso Creek Road, Aliso Viejo, CA 92656. Phone, (800) 899–1712 or (949) 362–2050 (ext 532); fax, (949) 362–2049; email, [email protected].

Supplementary data